Coupled Indoor Navigation for People Who Are Blind

Nanavati, Amal; Tan, Xiang Zhi; Steinfeld, Aaron

doi:10.1145/3173386.3176976

Cited by 13 publications

(2 citation statements)

References 4 publications

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“…However, the system consumed more energy and also required internet connection and as such not suitable in outdoor environment. Also, Nanavati, Tan, & Steinfeld [14] developed an indoor activities device for the visually impaired persons. The device was an autonomous navigating system, which helped the visually impaired in navigation.…”

Section: Related Workmentioning

confidence: 99%

A Smart Real-Time Standalone Route Recognition System for Visually Impaired Persons

Abdullahi¹,

Isah²,

Aliu³

et al. 2020

ComEngApp

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Visual Impairment is a common disability that results in poor or no eyesight, whose victims suffer inconveniences in performing their daily tasks. Visually impaired persons require some aids to interact with their environment safely. Existing navigation systems like electronic travel aids (ETAs) are mostly cloud-based and rely heavily on the internet and google map. This implies that systems deployment in locations with poor internet facilities and poorly structured environments is not feasible. This paper proposed a smart real-time standalone route recognition system for visually impaired persons. The proposed system makes use of a pedestrian route network, an interconnection of paths and their associated route tables, for providing directions of known locations in real-time for the user. Federal University of Technology (FUT), Minna, Gidan Kwanu campus was used as the case study. The result obtained from testing of the device search strategy on the field showed that the complexity of the algorithm used in searching for paths in the pedestrian network is , at worst-case scenario, where N is the number of paths available in the network. The accuracy of path recognition is 100%. This implies that the developed system is reliable and can be used in recognizing and navigating routes by the visual impaired in real-time.

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Section: Related Workmentioning

confidence: 99%

A Smart Real-Time Standalone Route Recognition System for Visually Impaired Persons

Abdullahi¹,

Isah²,

Aliu³

et al. 2020

ComEngApp

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show abstract

“…In recent years, researchers have continuously attempted to use guided robots to help blind people navigate and improve their quality of life. Multi-form and multifunctional guide robots continue to enter the public eye, among which the most representative one is mobile guidance robots [1][2][3]. Timely detection of dynamic and static obstacles and accurate identification of signal lights is one of the key technologies for guidance robots and is a necessity to assist blind people with safe travel [4].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Deep Learning Model for Obstacle and Traffic Light Detection Based on YOLOv5

Zhang

Yang

2023

Electronics

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Timely detection of dynamic and static obstacles and accurate identification of signal lights using image processing techniques is one of the key technologies for guidance robots and is a necessity to assist blind people with safe travel. Due to the complexity of real-time road conditions, current obstacle and traffic light detection methods generally suffer from missed detection and false detection. In this paper, an improved deep learning model based on YOLOv5 is proposed to address the above problems and to achieve more accurate and faster recognition of different obstacles and traffic lights that the blind may encounter. In this model, a coordinate attention layer is added to the backbone network of YOLOv5 to improve its ability to extract effective features. Then, the feature pyramid network in YOLOv5 is replaced with a weighted bidirectional feature pyramid structure to fuse the extracted feature maps of different sizes and obtain more feature information. Finally, a SIoU loss function is introduced to increase the angle calculation of the frames. The proposed model’s detection performance for pedestrians, vehicles, and traffic lights under different conditions is tested and evaluated using the BDD100K dataset. The results show that the improved model can achieve higher mean average precision and better detection ability, especially for small targets.

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Development and application of key technologies for Guide Dog Robot: A systematic literature review

Hong

Lin

Chen

et al. 2022

Robotics and Autonomous Systems

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Coupled Indoor Navigation for People Who Are Blind

Cited by 13 publications

References 4 publications

A Smart Real-Time Standalone Route Recognition System for Visually Impaired Persons

A Smart Real-Time Standalone Route Recognition System for Visually Impaired Persons

An Enhanced Deep Learning Model for Obstacle and Traffic Light Detection Based on YOLOv5

Development and application of key technologies for Guide Dog Robot: A systematic literature review

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